125 / 2019-12-15 00:36:00

Improved sparse error recovery approach for detecting QAM signals in overloaded massive MIMO systems

Massive MIMO (m-MIMO); Signal detection; Convex optimization; ADMM; Greedy algorithms; Compressive sensing

IEEE SAM 2020: Special Sessions > Dependent Source Separation

With a convenient concatenation of a convex relaxation-based detector and a simple greedy algorithm, we propose an improved Sparse error Recovery Detection approach (PDSR) for massive Multiple Input Multiple Output (m-MIMO) systems that, in particular, transmit QAM signals. The proposed PDSR approach can perform well in situations, where the classical one, either acts poorly or completely fails. We further propose an Alternating Direction Method of Multipliers (ADMM)-based solver for the convex detector, which is advantageous in maintaining an affordable complexity to the overall proposed detection scheme. Numerical experiments show the efficiency of our approach, especially when applied to overloaded m-MIMO systems.